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Posts Tagged ‘ splines ’

A primary problem data scientists face again and again is: how to properly adapt or treat variables so they are best possible components of a regression. Some analysts at this point delegate control to a shape choosing system like neural nets. I feel such a choice gives up far too much statistical rigor, transparency and
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On http://www.bakadesuyo.com, there was recently an interesting discussion about infidelity, the key question being "at what ages are men and women most likely to have affairs?" The discussion is based on some graphs, e.g.
The source is a paper b...

Statistical Methods for the Chain Ladder Technique Revisited: Source: Statistical Methods for the Chain Ladder Technique Demo
Background Forecasting outstanding claims and setting up suitable reserves to meet these claims is an important part of the b...

As Mark Twain said "the
art of prophecy is very difficult, especially about the future" (well, actually I am not sure Mark Twain was the first one to say so,
but if you're interested by that sentence, you can look here). I have been rather su...

Splines in regression is something which looks like a black box (or
maybe like some dishes you get when you travel away from home: it tastes
good, but you don't what's inside... even if you might have some clues,
you never know for sure*). With
spl...

We've seen in the previous post (here) how important the *-cartesian
product to model joint effected in the regression. Consider the case of
two explanatory variates, one continuous (, the age of the driver) and one qualitative (, gasoline ve...